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A Data‐Driven Examination of Apathy and Depression in Cognitively Normal Older Adults
Get PDFBackground:
Apathy and mood symptoms are increasingly recognised as clinical important aspects of prodromal dementia; both are associated with increased risk of dementia even in cognitively normal people. The clinical overlap between apathy and low mood poses a challenge in distinguishing between the two conditions. It is crucial to differentiate between depression and apathy, along with any underlying syndromes, to facilitate the development of targeted treatments. Using a data-driven approach, we recently reported the existence of distinct apathy and depression clusters in dementia, confirming observations from the clinic and epidemiology. In this study we sought to establish whether similar patterns of symptoms were present in cognitively normal older adults
Method:
We analysed data from 21,925 community dwelling older adults. Latent class analysis (LCA) was applied to self-reported and proxy ratings (obtained using the Mild Behavioral Impairment Checklist) of apathy and mood. Polygenic Risk Scores for Alzheimer’s disease (AD) and Major Depression (MDD) were tested for associated with class membership.
Result:
The LCA analysis using proxy data showed a 4-class group which was considered the best model: No symptoms, Depression, Apathy/depression, and an Apathy group. The LCA using self-reported data reveals the 4-class group without a as a clear apathy class as the proxy data (see Figures 1 and 2). PRS for AD and MDD were only associated with depression and apathy/depression classes in self-reported data (not in proxy data).
Conclusion:
This analysis highlights the apathy phenotype as a unique and separate condition, underscoring the imperative for additional research in this area. This emphasizes the potential for innovative approaches to delve deeper into the exploration and comprehension of apathy. The differences between the self and proxy reported data highlights the possibility of under reporting of apathy by patients
Predictive handover mechanism for seamless mobility in 5G and beyond networks
Get PDFData Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request. The datasets generated during and/or analyzed during the current study are not publicly available due to reasons such as privacy concerns, proprietary restrictions etc., but may be available from the corresponding author upon request.Scalability is one of the important parameters for mobile communication networks of the present generation and further to the future 5G and beyond networks. When a user is in motion transferring from one cell site to another, then the handover procedure becomes important in the sense that it ensures that a user gets consistent connection without interruption. Nevertheless, the classic handover process in cellular networks has some sort of drawback like causing service interruptions, affecting packet transmission, and increased latency which is highly uncongenial to the evolving applications which have stringent requirement to latency. To overcome these challenges and improve the mobile handover in 5G and future mobile networks, this article puts forth a predictive handover mechanism using reinforcement learning algorithm. The RL algorithm outperforms the ML algorithm in several aspects. Compared to ML, RL has a higher handover success rate (∼95% vs. ∼90%), lower latency (∼30 ms vs. ∼40 ms), reduced failure rate (∼5% vs. ∼10%), and shorter disconnection time (∼50 ms vs. ∼70 ms). This demonstrates the RL algorithm's superior ability to adapt to dynamic network conditions.Brunel University of London
Resemblance and Discrimination in Elections
Get PDFData Availability: Replication files are available in the JOP Dataverse (https://dataverse.harvard.edu/dataverse/jop).
The empirical analysis has been successfully replicated by the JOP replication analyst. Supplementary material is available in the online edition.Discrimination affects hiring, mating and voting decisions. Whilst discrimination in elections mainly relates to gender or race, we introduce a novel source of discrimination: candidate resemblance. When candidates’ partisanship is not known, voters select those that resemble most elected co-partisans. Using a machine learning algorithm for face comparison among white male legislators, we find a stronger resemblance effect for
Republicans compared to Democrats in the US. This happens because Republicans have a higher within-party facial resemblance than Democrats, even when accounting for gender and race. We find a similar pattern in the UK, where Conservative MPs are more similar looking to each other than Labour. Using a survey experiment, we find that Tory voters reward resemblance, while there is no similar effect for Labour. The results are consistent with an interpretation of this behaviour as a form of statistical discrimination.Raluca L Pahontu acknowledges financial support from the Department of Politics and International Relations at the University of Oxford, and London School of Economics and Political Science
Exergy analysis of the lean-burn hydrogen-fuelled engine
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Data will be made available on request.Hydrogen is considered an alternative fuel for use in internal combustion engines. The internal combustion engine will likely remain in use for vehicle and stationary applications for the foreseeable future, therefore identifying and quantifying efficiency losses of burning fuels is important. Exergy analysis is a method for investigating the fundamental origins of losses, the limits to efficiency, and the engineering trade-offs required to reduce losses. This comprehensive exergy analysis of a boosted lean-burn hydrogen spark ignition engine investigates the processes involving exergy destruction under real-world conditions. This efficiency of a hydrogen SI engine and the NO emissions are evaluated by quantifying the exergy destruction for various intake manifold air pressures, lean-burn mixtures, compression ratios, and spark timings. Using an improved two-zone engine model to study in-cylinder processes, the results indicate that increasing air dilution enhances exergy transfer to work, due mainly to diverting exhaust exergy into reversible work. However, increasing air dilution also increases combustion-related exergy destruction due to greater entropy generation for leaner mixtures, but reducing heat loss decreases combustion-related irreversibility. Higher manifold air pressures and compression ratios increase the quantity of exergy directed to work and heat, whilst reducing exergy expelled to exhaust. Gaining understanding of the detail of thermodynamic mechanisms of the routes by which the work potential is lost potentially assists in engineering improvements to minimize exergy losses, and to increase efficiency and work output
The finance-growth nexus and public-private ownership of banks in Brazil since 1870
Get PDFSupplementary Information is available online at: https://link.springer.com/article/10.1007/s10479-024-05924-7#Sec13 .How does finance affect economic growth? And does ownership matter? This paper investigates whether and how deposits in public vis-a-vis in private banks affect economic growth. It uses the power-ARCH framework with annual time series for Brazil from 1870 to 2018. There are three main findings: (a) the indirect impact of domestic financial development on economic growth is negative, whereas that of international financial development is positive, (b) the direct short-run effect of public and private banks is negative, while only for the latter does the positive direct long-run effect dominate, and (c) the indirect and direct short-run effect of public ownership banks is greater in size than that of private ownership banks.The authors did not receive support from any organization for the submitted work
Bank Risk, Capital Adequacy and Banking Market Concentration – A Global Study
Get PDFThis paper was developed from Samsher’s dissertation for the MSc degree in Banking and Finance in year 2023-24 for which Professor Davis was the supervisor.JEL codes: E58, G28.We examine the dynamic relationship between banking sector capital adequacy, competition, and financial risk in an extensive global macro-financial dataset of 220 countries covering the years 1998 to 2021, using Generalised Method of Moments (GMM) and Logit models. Developing from the earlier work by Davis et al (2020), the study underlines not only the essential role of capital adequacy measured with and without risk adjustment in reducing financial risk, but also the key influence of competition as proxied by market structure in influencing financial stability. Macroeconomic factors such as GDP growth, inflation, and unemployment are also shown to have an important effect on bank risk. The findings offer crucial perspectives for policymakers and regulators, emphasising the need of strict capital regulation that considers regional and historical economic factors as well as banking market structure in order to enhance the resilience of the banking industry and reduce the risk of financial crises.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors
Enhancing the trustworthiness of pain research: A call to action
Get PDFPerspective: Multiple challenges can adversely impact the trustworthiness of pain research and health research more broadly. We present ENTRUST-PE, a novel, integrated framework for more trustworthy pain research with recommendations for all stakeholders in the research ecosystem, and make a call to action to the pain research community.Acknowledgement: As a summary of the key issues discussed and the recommendations of the ENTRUST-PE project some passages of text are included from the full white paper of the project [69]. N.E. O’Connell, J. Belton, G. Crombez, et al.
ENTRUST-PE: An Integrated Framework for Trustworthy Pain Evidence
OSF Preprints (2024), 10.31219/osf.io/e39ys .Highlights:
• ENTRUST-PE is a new integrated framework for more trustworthy evidence in pain.
• ENTRUST-PE establishes seven core values that underpin trustworthy research.
• ENTRUST-PE makes recommendations for all stakeholders to improve trustworthiness.Perspective:
Multiple challenges can adversely impact the trustworthiness of pain research and health research more broadly. We present ENTRUST-PE, a novel, integrated framework for more trustworthy pain research with recommendations for all stakeholders in the research ecosystem, and make a call to action to the pain research community.The personal, social and economic burden of chronic pain is enormous. Tremendous research efforts are being directed toward understanding, preventing, and managing chronic pain. Yet patients with chronic pain, clinicians and the public are sometimes poorly served by an evidence architecture that contains multiple structural weaknesses. These include incomplete research governance, a lack of diversity and inclusivity, inadequate stakeholder engagement, poor methodological rigour and incomplete reporting, a lack of data accessibility and transparency, and a failure to communicate findings with appropriate balance. These issues span pre-clinical research, clinical trials and systematic reviews and impact the development of clinical guidance and practice. Research misconduct and inauthentic data present a further critical risk. Combined, they increase uncertainty in this highly challenging area of study and practice, drive the provision of low value care, increase costs and impede the discovery of more effective solutions.
In this focus article, we explore how we can increase trust in pain science, by examining critical challenges using contemporary examples, and describe a novel integrated conceptual framework for enhancing the trustworthiness of pain science. We end with a call for collective action to address this critical issue.The ENTRUST-PE project (www.entrust-pe.org), on which this article is based, was funded by the Federal Ministry of Education and Research, Germany under the ERA-NET Neuron Co-Fund Scheme (Proposal ID NEURON_NW-016)
Crystal Chemistry at Interfaces Between Liquid Al and Polar SiC{0001} Substrates
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The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.Silicon carbide (SiC) has been widely added into light metals, e.g., Al, to enhance their mechanical performance and corrosion resistance. SiC particle-reinforced metal matrix composites (SiC-MMCs) exhibit low weight/volume ratios, high strength/hardness, high corrosion resistance, and thermal stability. They have potential applications in aerospace, automobiles, and other specialized equipment. The macro-mechanical properties of Al/SiC composites depend on the local structures and chemical interactions at the Al/SiC interfaces at the atomic level. Moreover, the added SiC particles may act as potential nucleation sites during solidification. We investigate local atomic ordering and chemical interactions at the interfaces between liquid Al (Al(l) in short) and polar SiC substrates using ab initio molecular dynamics (AIMD) methods. The simulations reveal a rich variety of interfacial interactions. Charge transfer occurs from Al(l) to C-terminating atoms (Δq = 0.3e/Al on average), while chemical bonding between interfacial Si and Al(l) atoms is more covalent with a minor charge transfer of Δq = 0.04e/Al. The prenucleation at both interfaces is moderate with three to four recognizable layers. The information obtained here helps increase understanding of the interfacial interactions at Al/SiC at the atomic level and the related macro-mechanical properties, which is helpful in designing novel SiC-MMC materials with desirable properties and optimizing related manufacturing and machining processes.EPSRC (UK) under grant number EP/V011804/1 and EP/S036296/1
Test-retest Reliability of Diffuse Optical Tomography in a VR set-up in Neurodiverse Children
No full textSee Fr-085, Tailoring fNIRS and Virtual Reality for Use with Neurodiverse Children, for more details.This study aims to assess the replicability of of diffuse optical tomography (DOT) implemented in a VR set-up in
neurodevelopmental populations, with particular attention to neurodiverse children.RESPECT 4 Neurodevelopment project ref: R4N2023, Learning to Care – The Early Development of Empathy in Brain and Behaviour (RESPECT 4 Neurodevelopment stands for Responsible, Reliable, Scalable and Personalised Neurotechnologies for infants and children with neurodevelopmental conditions. It is a EPSRC/ MRC funded UKRI-Network Plus that started in September 2022 and will be funded until August 2025)
Cation Effect of Bio‐Ionic Liquid‐Based Electrolytes on the Performance of Zn‐Ion Capacitors
Get PDFData Availability Statement: The data that support the findings of this study are openly available in Figshare at 10.17633/rd.brunel.24635118, reference number 24635118.Supporting Information is available online at: https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/celc.202400511#support-information-section .Zn-ion capacitors (ZICs) are emerging as promising energy storage devices due to their low cost. Currently, aqueous-based electrolytes are primarily used in ZIC which have shown issues related to low Zn deposition/stripping efficiencies, and Zn dendrites formation, resulting in device failure. To overcome these issues and to develop environmentally benign energy storage devices, here we have studied bio-ionic liquid electrolytes (bio-ILs) in both symmetric and asymmetric capacitors. Choline acetate (ChOAc) and betaine acetate (BetOAc) in water were investigated as electrolytes for capacitors in the presence and absence of Zn salts. Spectroscopic analysis showed that Zn solvation in the electrolytes changes significantly with the change in cation which affects the electrochemical reactions and capacitor performance. Raman analysis showed the Zn complex formed in the case of ChOAc is [Zn(OAc)4]2− whereas for BetOAc is [Zn(OAc)5]3− thereby the Zn deposition/stripping in ChOAc-based electrolyte is quite stable whereas in case of BetOAc, Zn deposition/stripping is unstable. In the ChOAc electrolyte, the Zn/activated carbon asymmetric cell showed a capacity of >90 F g−1 at 0.1 A g−1 and a capacitance close to 40 F g−1 at 0.5 A g−1 with ∼82 % capacity retention after 3000 cycles, whereas BetOAc could only be used in symmetric cell capacitor. This study shows that bio-ILs can be used as sustainable electrolytes in energy storage devices wherein the cation plays a significant role in the capacitor performance.EPSRC, EP/W015129/1
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